Detecting regime change in computational finance : (Record no. 257119)

000 -LEADER
fixed length control field 03106nam a2200349 i 4500
003 - CONTROL NUMBER IDENTIFIER
control field TH-BaBU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240710091413.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200620s2021 flua fob 001 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
Transcribing agency TH-BaBU
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781003087595 (electronic book)
International Standard Book Number 9780367536282
050 04 - LIBRARY OF CONGRESS CALL NUMBER
Classification number HG176.7
Item number .C44 2021
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Chen, Jun,
Dates associated with a name 1990-,
Relator term author.
245 10 - TITLE STATEMENT
Title Detecting regime change in computational finance :
Remainder of title data science, machine learning and algorithmic trading /
Statement of responsibility, etc. Jun Chen, Edward P K Tsang.
250 ## - EDITION STATEMENT
Edition statement First edition.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Boca Raton, Fla. :
Name of producer, publisher, distributor, manufacturer CRC Press,
Date of production, publication, distribution, manufacture, or copyright notice 2021.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource.
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc. "Based on interdisciplinary research into "Directional Change", a new data-driven approach to financial data analysis, Detecting Regime Change in Computational Finance: Data Science, Machine Learning and, Algorithmic Trading applies machine learning to financial market monitoring and algorithmic trading. Directional Change is a new way of summarizing price changes in the market. Instead of sampling prices at fixed intervals (such as daily closing in time series), it samples prices when the market changes direction ("zigzag"). By sampling data in a different way, the book lays out concepts which enable the extraction of information that other market participants may not be able to see. The book includes a Foreword by Richard Olsen and explores the following topics: Data science: as an alternative to time series, price movements in a market can be summarised as directional changes Machine learning for regime change detection: historical regime changes in a market can be discovered by a Hidden Markov Model Regime characterisation: normal and abnormal regimes in historical data can be characterised using indicators defined under Directional Change Market Monitoring: by using historical characteristics of normal and abnormal regimes, one can monitor the market to detect whether the market regime has changed Algorithmic trading: regime tracking information can help us to design trading algorithms It will be of great interest to researchers in computational finance, machine learning, and data science"--
Assigning source Provided by publisher.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Background and literature survey -- Regime change detection using directional change indicators -- Classification of normal and abnormal regimes in financial markets -- Tracking regime changes using directional change indicators -- Algorithmic trading based on regime change tracking.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Financial engineering
General subdivision Methodology.
Topical term or geographic name entry element Finance
General subdivision Mathematical models.
Topical term or geographic name entry element Stocks
General subdivision Prices
-- Mathematical models.
Topical term or geographic name entry element Hidden Markov models.
Topical term or geographic name entry element Expectation-maximization algorithms.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Tsang, Edward,
Relator term author.
856 41 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2576634">https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2576634</a>
Public note Electronic Resources
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type E-Book

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